To achieve this we develop REDO. As illustrated in Fig. REF , REDO predicts the shape of different objects (, human, animals, car) and models their dynamics (, articulation, non-rigid motion, rigid motion) given input video clips. Besides the RGB frames, REDO takes as input the depth map, masks of the objects of interest, and camera matrices. In practice these inputs are realistic as depth-sensors are increasingly prevalent [1]}, [2]} and as segmentation models [3]}, [4]} are increasingly accurate and readily available, , on mobile devices. If this data isn't accessible, off-the-shelf tools are applicable (, SfM [5]}, instance segmentation [6]}, video depth estimation [7]}).
